Voice disorders affect approximately 6.6% of the working-age population in the United States. Many common voice disorders are chronic or recurring conditions that are likely to result from faulty and/or abusive patterns of vocal behavior referred to generically as vocal hyperfunction. Such behaviorally based disorders can be difficult to accurately assess in the clinical setting and could potentially be much better characterized by long-term ambulatory monitoring of vocal function as individuals engage in their typical daily activities. Devices that use a neck-placed miniature accelerometer (ACC) as a phonation sensor have shown the best potential for unobtrusive long-term monitoring of vocal function. The adoption, however, of this technology into clinical practice has been quite limited because of: 1) technical limitations of current devices, measures, and analysis algorithms; 2) the relatively high cost of commercially-available systems; and 3) the lack of statistically robust studies to determine the true diagnostic capabilities of ACC-based measures. The overall goal of the proposed project (in response to PAR-09-057) is to develop ACC-based ambulatory monitoring of vocal function into a valid, reliable, and cost-effective clinical tool that can be used to accurately identify and differentiate patterns of voice use that are associated with hyperfunctional voice disorders. Achieving this goal will: 1) greatly improve clinical assessment of these commonly-occurring types of voice disorders, 2) enable voice therapy to more accurately target specific hyperfunctional behaviors for individual patients, and 3) provide the basis for future efforts to develop ambulatory biofeedback approaches that have the potential to facilitate more efficient and effective behavioral treatment of these disorders. In the R21 phase of this project we will develop and validate a new, versatile, and cost-effective system for ambulatory voice monitoring that uses a neck-placed miniature ACC as the phonation sensor and a mobile personal digital device (e.g., a smartphone) as the data acquisition platform. An effort will be made to facilitate the continued availability of this technology for clinical use and development by designing system software and basic interface circuitry that is largely compatible with new generations of personal digital device architecture. The R33 phase of the project will focus on using the new ambulatory monitoring system to collect data from a large, statistically robust sample of patients with hyperfunctional voice disorders (before and after treatment) and matched controls. These data will be subjected to three types of analysis approaches in an effort to identify the best set of measures for differentiating among hyperfunctional and normal patterns of vocal behavior: 1) previously-developed ambulatory measures of vocal function that include vocal dosage; 2) measures based on estimates of glottal airflow that are extracted from the ACC signal using a new vocal system model, and 3) measures based on methods that have been used successfully in analyzing long-term recordings of other physiologic signals (e.g., electrocardiograms) for risk stratification of patients.